Unlike the RGB and CMYK color models, Lab color is designed to approximate human vision. It aspires to perceptual uniformity, and its L component closely matches human perception of lightness. It can thus be used to make accurate color balance corrections by modifying output curves in the a and b components, or to adjust the lightness contrast using the L component. These transformations are difficult or impossible in the RGB or CYMK spaces, which model the output of physical devices, rather than human visual perception.

Because Lab space is much larger than the gamut of computer displays, printers, or even human vision, a bitmap image represented as Lab requires more data per pixel to obtain the same precision as an RGB or CMYK bitmap. In the 1990s, when computer hardware and software was mostly limited to storing and manipulating 8 bit/channel bitmaps, converting an RGB image to Lab and back was a lossy operation. With 16 bit/channel support now common, this is no longer such a problem.

Additionally, many of the “colors” within Lab space fall outside the gamut of human vision, and are therefore purely imaginary; these “colors” cannot be reproduced in the physical world. Though color management software, such as that built in to image editing applications, will pick the closest in-gamut approximation, changing lightness, colorfulness, and sometimes hue in the process, author Dan Margulis claims that this access to imaginary colors is useful going between several steps in the manipulation of a picture.[6]

Unlike the RGB and CMYK color models, Lab color is designed to approximate human vision. It aspires to perceptual uniformity, and its L component closely matches human perception of lightness. It can thus be used to make accurate color balance corrections by modifying output curves in the a and b components, or to adjust the lightness contrast using the L component. These transformations are difficult or impossible in the RGB or CYMK spaces, which model the output of physical devices, rather than human visual perception.

Because Lab space is much larger than the gamut of computer displays, printers, or even human vision, a bitmap image represented as Lab requires more data per pixel to obtain the same precision as an RGB or CMYK bitmap. In the 1990s, when computer hardware and software was mostly limited to storing and manipulating 8 bit/channel bitmaps, converting an RGB image to Lab and back was a lossy operation. With 16 bit/channel support now common, this is no longer such a problem.

Additionally, many of the “colors” within Lab space fall outside the gamut of human vision, and are therefore purely imaginary; these “colors” cannot be reproduced in the physical world. Though color management software, such as that built in to image editing applications, will pick the closest in-gamut approximation, changing lightness, colorfulness, and sometimes hue in the process, author Dan Margulis claims that this access to imaginary colors is useful going between several steps in the manipulation of a picture.[6]

Unlike the RGB and CMYK color models, Lab color is designed to approximate human vision. It aspires to perceptual uniformity, and its L component closely matches human perception of lightness. It can thus be used to make accurate color balance corrections by modifying output curves in the a and b components, or to adjust the lightness contrast using the L component. These transformations are difficult or impossible in the RGB or CYMK spaces, which model the output of physical devices, rather than human visual perception.

Because Lab space is much larger than the gamut of computer displays, printers, or even human vision, a bitmap image represented as Lab requires more data per pixel to obtain the same precision as an RGB or CMYK bitmap. In the 1990s, when computer hardware and software was mostly limited to storing and manipulating 8 bit/channel bitmaps, converting an RGB image to Lab and back was a lossy operation. With 16 bit/channel support now common, this is no longer such a problem.

Additionally, many of the “colors” within Lab space fall outside the gamut of human vision, and are therefore purely imaginary; these “colors” cannot be reproduced in the physical world. Though color management software, such as that built in to image editing applications, will pick the closest in-gamut approximation, changing lightness, colorfulness, and sometimes hue in the process, author Dan Margulis claims that this access to imaginary colors is useful going between several steps in the manipulation of a picture.[6]

a lot of theoretical info with nil practical info ~

DRY吹唔做~ 呃錢~

Better than you! You haven't even said anything about lab color other than you wouldn't tell us